[V1] Remove V0 code paths for Hybrid models (#25400)

Signed-off-by: Thomas Parnell <tpa@zurich.ibm.com>

vllm/model_executor/models/lfm2.py

@@ -8,7 +8,6 @@ import torch
 import torch.nn as nn
 from transformers import Lfm2Config
 
-from vllm import envs
 from vllm.attention import Attention
 from vllm.compilation.decorators import support_torch_compile
 from vllm.config import CacheConfig, ModelConfig, VllmConfig
@@ -297,7 +296,6 @@ class Lfm2ShortConvDecoderLayer(nn.Module):
         self.conv(
             hidden_states,
             output,
-            conv_metadata=None,
         )
         hidden_states, residual = self.ffn_norm(output, residual)
         hidden_states = self.feed_forward(hidden_states)
@@ -459,13 +457,11 @@ class Lfm2ForCausalLM(nn.Module, HasInnerState, SupportsLoRA, SupportsPP,
     def get_mamba_state_shape_from_config(
         cls,
         vllm_config: "VllmConfig",
-        use_v1: bool = True,
     ) -> tuple[tuple[int, int]]:
         """ Calculate shapes for LFM2's convolutional cache.
 
         Args:
             vllm_config: vLLM config
-            use_v1: Get shapes for V1 (or V0)
 
         Returns:
             Tuple containing:
@@ -478,7 +474,6 @@ class Lfm2ForCausalLM(nn.Module, HasInnerState, SupportsLoRA, SupportsPP,
             tp_world_size=parallel_config.tensor_parallel_size,
             intermediate_size=hf_config.conv_dim,
             conv_kernel=hf_config.conv_L_cache,
-            use_v1=use_v1,
         )
 
     def __init__(self, *, vllm_config: VllmConfig, prefix: str = "") -> None:
@@ -489,8 +484,6 @@ class Lfm2ForCausalLM(nn.Module, HasInnerState, SupportsLoRA, SupportsPP,
         scheduler_config = vllm_config.scheduler_config
         assert (not cache_config.enable_prefix_caching
                 ), "Lfm2 currently does not support prefix caching"
-        assert envs.VLLM_USE_V1, (
-            "Lfm2ForCausalLM doesn't support vLLM v0. Please enable v1")
 
         super().__init__()
         self.config = config